The Effect Of Consumer Confusion Proneness On Word Of Mouth, Trust, and Customer Satisfaction Malisa Rosadi dan Fandy Tjiptono
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Ambiguity confusion
Ambiguity confusion is “ consumers’ tolerance for processing unclear, misleading, or ambiguous products,
product-related information or advertisements” Walsh, Hennig-Thurau and Mitchell, 2007, p. 705. In an earlier work, Mitchell, Walsh and Yamin 2005 used the term “unclarity confusion” to refer to this type of confusion. In
general, ambiguity confusion may arise from four factors: technological complexity, ambiguous informationdubious product claims, conflicting information, and incorrect interpretation Leek and Kun, 2006.
When consumers face multiple interpretations of product quality from different sources, they can get confused. Such confusion can be even more problematic if the information is conflicting and inconsistent with the consumer’s
prior beliefs and knowledge. To overcome the confusion, a consumer may seek support or help from important others such as family members, friends, co-workers, experts, and so forth to establish which information is more
credible. Once they understand the ambiguity or conflicting information, they may share their new knowledge to others which in turn will increase their word of mouth Walsh, Hennig-Thurau and Mitchell, 2007. In their study,
Walsh and Mitchell 2010 found support for a significant positive impact of ambiguity confusion proneness on word of mouth. As a result, hypothesis 7 is formulated as follows:
H
7
.
Ambiguity confusion proneness has a signifi cant positive impact on consumer word of mouth. Inability to choose among many very similar products with ambiguous information about their differences
may cause confusion and frustration which lead to purchase decision delay. Consumers are likely to take time to overcome some of their confusion. In addition to uncertain feeling, in some situations ambiguity is likely to cause
consumers to suspect that the companies providing conflicting product information attempt to take advantage of them. As a result, ambiguity-prone consumers may have less trust in the companies and their products. Following
the original formulation in Walsh and Mitchell 2010, hypothesis 8 is stated as follows:
H
8
.
Ambiguity confusion proneness has a signifi cant negative impact on consumer trust. Complex and ambiguous information is likely to cause consumers to be uncertain and anxious as to which
information to believe. To reduce the ambiguity, consumers need extra time, efforts and sometimes money to obtain the needed additional information. Such extra processing will result in the reduction of consumers’ satisfaction
with the companies and products. As argued in Walsh and Mitchell 2010, this reasoning leads to the following hypothesis 9:
H
9
.
Ambiguity confusion proneness has a signifi cant negative impact on macro satisfaction.
3. RESEARCH METHOD
3.1. Research context
A survey using self-administrative questionnaires was conducted to address the research question of interest. The research context of the present study is how consumer confusion proneness affects word of mouth, trust,
and customer satisfaction. While most consumer confusion studies have been focused on the Western cultures context with exceptions of Thailand, South Korea, China, and India, the present study investigates similar issue
in the Indonesian context—one of the most populated countries in the world. The specific research procedures were modified and replicated from Walsh and Mitchell 2010 who studied consumer confusion proneness effects
in Germany.
Nevertheless, the product context is different from the general unspecified product category investigated in Walsh and Mitchell 2010. The present study focuses on the Indonesian smartphone market. The specific product
KINERJA Volume 17, No.1, Th. 2013 Hal. 81-93
86 was chosen to address to the research call recommended by Walsh, Hennig-Thurau and Mitchell 2007. They
suggested a further study to test their consumer confusion proneness in a specific product context. Another reason is that respondents are more likely to better understand the topic if a specific product in this
case, smartphones is provided. Mass media has reported that the popularity of smartphones has grown rapidly in Indonesia see for instance, Suling, 2010; www.suarapembaruan.com 3 January 2012; Firman and Sukirno,
2012. Although there is no generally accepted definition of the term ‘smartphone’, generally a smartphone is ” a
phone that has extra functionality and advanced application so that it is almost like a small computer or more of a mini portable computer” www.smartphonebasics.com, accessed on 12 January 2012; see Figure 2 for examples
of smartphones. The ever growing features, applications, and operating systems of smartphones may cause consumers to be confused as to which brand to choose. Therefore, it is a relevant and appropriate context for
studying consumer confusion.
Source: Sunny 2011
Figure 2. Examples of Smartphones
3.2 Sample and sampling methods
While Walsh and Mitchell 2010 used 355 German shoppers in a major northern German city as their samples, the present study focuses on university students in the Daerah Istimewa Yogyakarta DIY. Student samples were
used because smartphone users in Indonesia are mostly those who aged between 18 to 24 years—university students Firman, 2010. A combination of convenience sampling and purposive sampling was used to select the
sample of university students in DIY in order to examine the hypotheses stated in the present study. The criterion used for the purposive sampling was university students who used andor owned a smartphone. This resulted in
150 university students participated in the survey.
3.3 Data collection
A structured questionnaire was used as the research instrument in this study. It consists of three parts. The first part was used to identify the respondent profiles in terms of their gender, university, and smartphone ownership.
The second part measuring consumer confusion proneness was adapted from Walsh, Hennig-Thurau and Mitchell’s 2007 scale. Respondents were asked to indicate the degree of their agreement with the three similarity
confusion proneness statements, four overload confusion proneness statements, and five ambiguous confusion proneness statements on a 5-point Likert scale ranging from 1 = “strongly disagree” to 5 = “strongly agree”. It is
important to note that the questionnaire items were adapted from a general unspecified product category context into the smartphone context. For example, the original statement of “
Products such as CD players or VCR often have so many features that a comparison of different brands is barely possible” was adjusted to “Smartphones
often have so many features that a comparison of different brands is barely possible”.
The Effect Of Consumer Confusion Proneness On Word Of Mouth, Trust, and Customer Satisfaction Malisa Rosadi dan Fandy Tjiptono
87 In the final section, respondents were asked to evaluate their levels of trust, satisfaction, and word of mouth. These
three behavioral consequences of consumer confusion proneness were adapted from Walsh and Mitchell 2010 and consisted of six word of mouth statements, three trust statements, and one satisfaction statement. A 5-point Likert scale
1 = “strongly disagree”, 5 = “strongly agree” was used for all statements.
4. ANALYSIS AND
DISCUSSION 4.1. Pro les of the respondents
There were 200 questionnaires distributed at four major universities in the Daerah Istimewa Yogyakarta, i.e. Universitas Atma Jaya Yogyakarta UAJY, Universitas Pembangunan Nasional UPN, Universitas Sanata
Dharma USD, and Universitas Kristen Duta Wacana UKDW. However, only 150 of them were returned and complete a response rate of 75. These 150 questionnaires were used for the analysis.
Respondent profiles are summarized in Table 1. It can be observed that female and male respondents were almost equal 50.67 and 49.33, respectively. UAJY students were dominant 59.33, followed by UPN
students 21.33, UKDW 12, and USD 7.33. It is apparent from Table 1 that all respondents had smartphones. BlackBerry, Nokia, and Samsung were the
top three, followed by iPhone, Sony, LG, and other brands. It is slightly different from the five most widely used smartphone brands in Indonesia based on the Nielsen survey cited in Karina, 2011: Nokia 41, Blackberry 21,
Samsung 9, Nexian 7, and Sony Ericsson 7 Karina, 2011.
Table 1. Profi les of Respondents
Description Number
Percentage Gender
Male Female
74 76
49.33 50.67
University
Universitas Atma Jaya Yogyakarta UAJY Universitas Pembangunan Nasional UPN
Universitas Sanata Dharma USD Universitas Kristen Duta Wacana UKDW
89 32
11 18
59.33 21.33
7.33 12
Smartphone Ownership
Blackberry Nokia
Samsung iPhone
Sony LG
Beyond HTC
Motorola 86
21 20
11
5 4
1 1
1 57.33
14 13.33
7.33 3.33
2.67 0.67
0.67 0.67
